Typical Responsibilities/Tasks:
• Develop and implement analytical techniques and applications that transform raw data into meaningful, actionable information supporting operational and program decision-making.
• Apply data mining, data modeling, statistical analysis, natural language processing (NLP), and machine learning techniques to analyze large structured and unstructured datasets.
• Use data-oriented programming languages and analytical tools to collect, process, integrate, analyze, and interpret complex datasets.
• Develop data models and algorithms to identify trends, patterns, relationships, anomalies, risks, and performance indicators.
• Create effective data visualizations, dashboards, and dynamic reports that communicate complex analytical findings to technical and non-technical stakeholders.
• Interpret analytical results and provide data-driven findings and recommendations to support system performance, readiness, reliability, maintainability, and operational availability.
• Integrate logistics, engineering, maintenance, reliability, and operational data to support lifecycle management and sustainment analysis.
• Develop and maintain repeatable analytical processes, models, and reporting solutions that improve data quality, consistency, traceability, and accessibility.
• Collaborate with logisticians, engineers, operations research analysts, and program personnel to translate mission and business requirements into analytical solutions.
• Prepare and present technical reports, analyses, visualizations, and briefings that enable timely, informed decision-making and continuous performance improvement.